Resampling variance estimation for complex survey data
Resampling variance estimation for complex survey data
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DOI：
10.1177/1536867x1001000201
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发表时间：
2010-01-01
期刊：
影响因子：
4.8
通讯作者：
Kolenikov, Stanislav
中科院分区：
文献类型：
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作者：
Kolenikov, Stanislav
在本文中，我讨论了在复杂调查数据中进行方差重抽样估计的主要方法：平衡重复复制、折刀和自举。均衡重复复制和刀切在状态下实现。svy套件。复杂测量数据的引导是通过bsweights命令实现的。我将描述这个命令并提供工作示例。
In this article, I discuss the main approaches to resampling variance estimation in complex survey data: balanced repeated replication, the jackknife, and the bootstrap. Balanced repeated replication and the jackknife are implemented in the State. svy suite. The bootstrap for complex survey data is implemented by the bsweights command. I describe this command and provide working examples.